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[Relay][Frontend][TensorFlow] Support BatchMatMul with input dimensions larger than 3 #3732

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merged 7 commits into from
Aug 14, 2019

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soiferj
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@soiferj soiferj commented Aug 8, 2019

This change adds support for BatchMatMul with n-dimensional inputs. For example, batch matrix multiplication of (2, 3, 4, 5) x (2, 3, 5, 4).

@soiferj soiferj closed this Aug 8, 2019
@soiferj soiferj reopened this Aug 8, 2019
@soiferj soiferj marked this pull request as ready for review August 8, 2019 06:15
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soiferj commented Aug 8, 2019

@srkreddy1238 and @alexeyr would you mind taking a look?

@soiferj soiferj changed the title [Relay][TensorFlow] Support BatchMatMul with input dimensions larger than 3 [Relay][Frontend][TensorFlow] Support BatchMatMul with input dimensions larger than 3 Aug 8, 2019
outer_dims = [orig_shape_x[i] for i in range(0, len(orig_shape_x) - 2)]
num_outer_elts = 1
for outer_dim in outer_dims:
num_outer_elts *= outer_dim
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Shouldn't this just call np.prod?

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Updated

_test_batch_matmul((2, 3, 4, 5, 6), (2, 3, 4, 6, 5), 'int32')
_test_batch_matmul((2, 3, 4, 5, 6), (2, 3, 4, 6, 5), 'float32', True, True)
_test_batch_matmul((2, 3, 4, 5, 6), (2, 3, 4, 5, 6), 'int32', True, False)
_test_batch_matmul((2, 3, 4, 5, 6), (2, 3, 4, 5, 6), 'float32', False, True)
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I'd prefer to have tests with different numbers of outer dimensions.

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Updated

@MarisaKirisame
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@soiferj how hard is it to make dense/batchmatmul to support more dimension instead?

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soiferj commented Aug 10, 2019

From looking around the code, it seems like a good amount of work. All of computes would have to change, and we would probably want to change all of the schedules as well. We would also have to find and remove all asserts that verify the number of dimensions. Is this a preferred solution? I don't think the reshapes will have much overhead.

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I see. Can you make this function universal then? (move this into relay/op, and allow other ppl to use it as well). I need this function badly.

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soiferj commented Aug 10, 2019

Sure! I can work on that.

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soiferj commented Aug 10, 2019

@alexeyr what do you think of the proposed change? Should we make this functionality a little more generic? If so, where do you think it should go?

Edit: never mind, I’m not going to make this change. Feel free to review as-is.

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soiferj commented Aug 11, 2019

@MarisaKirisame would you mind explaining what you want the interface to look like? Because I don’t know how all of the front ends look, I could make a method called ConvertTo3d. Then, converting back to the original dimensions would be handled by the front end (since it’s just one function call).

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@soiferj nevermind, I dont need it anymore, this is good to me.

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alexeyr commented Aug 12, 2019

@soiferj I'd reply that I can't evaluate at the moment anyway :) But it looks good to me.

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LGTM

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soiferj commented Aug 13, 2019

@tqchen @tmoreau89 would one of you be able to merge?

@tqchen tqchen merged commit 83bef9f into apache:master Aug 14, 2019
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tqchen commented Aug 14, 2019

Thanks @soiferj @alexeyr @MarisaKirisame !

wweic pushed a commit to neo-ai/tvm that referenced this pull request Aug 16, 2019
…ns larger than 3 (apache#3732)

* Support BatchMatMul with shapes greater than length 3

* Fixes

* Add tests

* Remove dependency on Python3

* Clean up

* Merge with master

* Resolve comments
@soiferj soiferj deleted the soiferj/batchmatmul4d branch August 22, 2019 16:31
anijain2305 pushed a commit to anijain2305/tvm that referenced this pull request Aug 22, 2019
…ns larger than 3 (apache#3732)

* Support BatchMatMul with shapes greater than length 3

* Fixes

* Add tests

* Remove dependency on Python3

* Clean up

* Merge with master

* Resolve comments
wweic pushed a commit to neo-ai/tvm that referenced this pull request Sep 6, 2019
…ns larger than 3 (apache#3732)

* Support BatchMatMul with shapes greater than length 3

* Fixes

* Add tests

* Remove dependency on Python3

* Clean up

* Merge with master

* Resolve comments
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4 participants